Non-invasive classification of severe sepsis and systemic inflammatory response syndrome using a nonlinear support vector machine: A preliminary study

Physiological Measurement

Volumn 31, Issue 6, 2010, Pages 775-793

  Tang, Collin H H ^a   Middleton, Paul M ^b,c,d   Savkin, Andrey V ^a   Chan, Gregory S H ^a   Bishop, Sarah ^c   Lovell, Nigel H ^e  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b PRINCE OF WALES HOSPITAL   (Australia)

^c UNIVERSITY OF NEW SOUTH WALES   (Australia)

^d Greater Sydney Area Helicopter Emergency Medical Service Ambulance Service New South Wales Rescue Helicopter Base Bankstown Airport   (Australia)

^e UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Photoplethysmography; Power spectrum analysis; Principal component analysis; Sepsis; Support vector machine

Indexed keywords

NEURONS; POWER SPECTRUM; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINES;

CLASSIFICATION RESULTS; NONLINEAR SUPPORT VECTOR MACHINES; POWER SPECTRUM ANALYSIS; PRINCIPAL-COMPONENT ANALYSIS; SEPSIS; SPECTRA ANALYSIS; SUPPORT VECTOR MACHINE CLASSIFIERS; SUPPORT VECTORS MACHINE; SYSTEMIC INFLAMMATORY RESPONSE SYNDROMES; SYSTEMIC RESPONSE;

SPECTRUM ANALYSIS;

ADULT; ALGORITHM; ANALYSIS OF VARIANCE; ARTIFICIAL INTELLIGENCE; AUTONOMIC NERVOUS SYSTEM; CLASSIFICATION; HUMAN; NONLINEAR SYSTEM; PATHOPHYSIOLOGY; RECEIVER OPERATING CHARACTERISTIC; RISK FACTOR; SEPSIS;

ADULT; ALGORITHMS; ANALYSIS OF VARIANCE; ARTIFICIAL INTELLIGENCE; AUTONOMIC NERVOUS SYSTEM; HUMANS; NONLINEAR DYNAMICS; RISK FACTORS; ROC CURVE; SEPSIS;

EID: 77952370942     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/31/6/004     Document Type: Article

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